Abstract

Abstract Several authors have shown the applicability of modified black oil (MBO) approach for modeling gas condensate and volatile oil reservoirs. It was shown before that MBO could adequately replace compositional simulation in many applications. In this work, a new set of MBO PVT correlations was developed. The four PVT functions (oil-gas ratio, Rv, solution gas-oil ratio, Rs, oil formation volume factor, Bo, and gas formation volume factor, Bg) were investigated. According to our knowledge, no other correlation for calculating oil-gas ratio exists in the petroleum literature. Alternatively, oil-gas ratio (needed for material balance and reservoir simulation calculations of gas condensate and volatile oil reservoirs) had to be generated from a combination of laboratory experiments and elaborate calculation procedures using EOS models. In previous work, we found that Whitson and Torp method for generating Modified Black Oil (MBO) PVT properties yielded best results when compared with compositional simulation. This method (and the others available in the literature such as Coats’ and Walsh's) requires the use of data from PVT laboratory experiments and proper construction of EOS models. We used Whitson and Torp's method to generate our database of the MBO PVT curves used in developing our correlations after matching the PVT experimental results with an EOS model. For each one of the four PVT parameters, we used 1850 values obtained from PVT analysis of eight gas condensate fluid samples and 1180 values obtained from PVT analysis of five volatile oil fluid samples. The samples were selected to cover a wide range of fluid composition, condensate yield, reservoir temperature, and pressure. The data points were generated by extracting the PVT properties of each sample at six different separator conditions. We then used multi-variable regression techniques to calculate our correlation constants. The new correlations were validated using the generalized material balance equation calculations with data generated from a compositional reservoir simulator. These new correlations depend only on readily available parameters in the field and can have wide applications when representative fluid samples are not available.

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